Some current medical devices designed to provide antitachycardia therapy and defibrillation therapy have attempted to discriminate between physiological (e.g., NSR) and pathological cardiac rhythms (e.g., SLVT) using the heart rate sensed by a single ventricular sensor. U.S. Pat. No. 4,875,483 to W. Vollmann et al, entitled "Implantable Cardiac Pacer with Programmable Antitachycardia Mechanisms", which issued on Oct. 24, 1989, discloses such a device. Others have attempted to discriminate between pathological cardiac rhythms requiring different therapies (e.g., FVT and SLVF), but having overlapping ventricular rates.
However, classification techniques which are based solely on ventricular rate parameters are unable to distinguish between physiological and pathological rhythms, or between different pathological rhythms that have overlapping ventricular rates. An important instance of this is NSR, which is a physiological rhythm, and SLVT, which is a pathological rhythm. A second important instance of this is FVT, which is a pathological rhythm which may be treated by antitachycardia pacing, and a SLVF, which is a pathological rhythm which must be treated by high voltage defibrillation shock.
The use of a neural network to match templates of different known rhythms with an unknown rhythm may overcome this particular problem. This is proposed in U.S. Pat. No. 5,092,343 to R. Spitzer et al, entitled "Waveform Analysis Apparatus and Method Using Neural Network Techniques", which issued on Mar. 3, 1992. The Spitzer et al. patent device offers only a partial solution to the above problem as it has an unacceptably long delay before reaching a decision and also an unacceptably high error rate. The reason for the long delay is that the device accumulates data to form a frequency histogram of signal amplitudes before beginning the next stage of the classification process. The device then divides the waveforms into different groups by means of frequency histograms each containing waveforms of similar amplitudes. The effect of this is to erroneously separate cardiac rhythms of the same type into different groups due to the variation in signal amplitude caused by respiration. Furthermore, the above device uses as the input, to a neural network contained therein, samples from the input waveforms, i.e. filtered signals with no features extracted. This is insufficient in terms of achieving a satisfactory classification accuracy.
Further prior art includes that described in an article written by Susan Lee entitled "Using a Translation--Invariant Neural Network to Diagnose Heart Arrhythmia", IEEE Engineering in Medicine and Biology 11th Annual Conference, Seattle, Wash., 1989. In this article, ventricular intracardiac electrograms (ICEG) underwent a translation invariance pre-processing by means of weighted sums of differences of signal samples before being passed to the input of the neural network. The theoretical advantage of this is that it is not necessary to accurately align each waveform with the neural network inputs. The disadvantage is that there is a loss of sensitivity and specificity and greatly increased processing time due to the multiplications required to calculate the weighted sums of differences.
An improved approach is described in the present invention in which signal peaks are used for alignment and the effect of jitter is removed by means of a simplified sums of differences procedure which does not require multiplications.
U.S. Pat. No. 5,251,626 issued Oct. 12, 1993 to P. Nickolls et al. for "Apparatus and Method for the Detection and Treatment of Arrhythmias Using a Neural Network" describes a system which includes a neural network having at least three hierarchical levels. A first lower level is used for classifying individual waveforms. A second higher level is used for diagnosing detected arrhythmias, and a third higher level operates for therapy application to a diagnosed arrhythmia. The present invention eliminates the need for a neural network at the first lower level and thereby provides a faster real time diagnosis of arrhythmias. Accordingly, the main object of this invention is to provide an improved apparatus and a method for discriminating among heart rhythms having overlapping ventricular rates on the basis of their morphology. The apparatus reliably discriminates between NSR and pathological rhythms, such as SLVTs and SVTs, and also reliably discriminates between other different pathological rhythms, such as FVT and SLVF, without undue delay and in such a way that the invention is suitable for use in an implantable cardioverter/defibrillator/pacemaker. Furthermore, real time classification is achieved with the present invention by aligning the extracted waveforms with the peaks of the signals from which they are extracted.
It is a further object of the invention to provide a classification technique which uses morphological features extracted from an electrogram as the input to a neural network.
It is a further object of the invention to provide a classification technique which continuously processes and classifies data.